1. Field of the Invention
The present invention relates to methods and apparatus for characterizing petroleum fluid extracted from a hydrocarbon bearing geological formation. The invention has application to reservoir simulation applications, although it is not limited thereto.
2. Description of Related Art
Petroleum consists of a complex mixture of hydrocarbons of various molecular weights, plus other organic compounds. The exact molecular composition of petroleum varies widely from formation to formation. The proportion of hydrocarbons in the mixture is highly variable and ranges from as much as 97% by weight in the lighter oils to as little as 50% in the heavier oils and bitumens. The hydrocarbons in petroleum are mostly alkanes (linear or branched), cycloalkanes, aromatic hydrocarbons, or more complicated chemicals like asphaltenes. The other organic compounds in petroleum typically contain carbon dioxide (CO2), nitrogen, oxygen, and sulfur, and trace amounts of metals such as iron, nickel, copper, and vanadium.
The alkanes, also known as paraffins, are saturated hydrocarbons with straight or branched chains which contain only carbon and hydrogen and have the general formula CnH2n+2. They generally have from 5 to 40 carbon atoms per molecule, although trace amounts of shorter or longer molecules may be present in the mixture. The alkanes include methane (CH4), ethane (C2H6), propane (C3H8), i-butane (iC4H10), n-butane (nC4H10), i-pentane (iC5H12), n-pentane (nC5H12), hexane (C6H14), heptane (C7H16), octane (C8H18), nonane (C9H20), decane (C10H22), hendecane (C11H24)—also referred to as endecane or undecane, dodecane (C12H26), tridecane (C13H28), tetradccane (C14H30), pentadecane (C15H32) and hexadecane (C16H34).
The cycloalkanes, also known as napthenes, are saturated hydrocarbons which have one or more carbon rings to which hydrogen atoms are attached according to the formula CnH2n. Cycloalkanes have similar properties to alkanes but have higher boiling points. The cycloalkanes include cyclopropane (C3H6), cyclobutane (C4H8), cyclopentane (C5H10), cyclohexane (C6H12), and cycloheptane (C7H14).
The aromatic hydrocarbons are unsaturated hydrocarbons which have one or more planar six-carbon rings called benzene rings, to which hydrogen atoms are attached with the formula CnHn. They lend to burn with a sooty flame, and many have a sweet aroma. Some are carcinogenic. The aromatic hydrocarbons include benzene (C6H6) and derivatives of benzene, as well as polyaromatic hydrocarbons.
Asphaltenes consist primarily of carbon, hydrogen, nitrogen, oxygen, and sulfur, as well as trace amounts of vanadium and nickel. The C:H ratio is approximately 1:1.2, depending on the asphaltene source. Asphaltenes have been shown to have a distribution of molecular masses in the range of 400 grams/mole to 1500 grams/mole with a maximum around 750 grams/mole. The chemical structure of asphaltene is difficult to ascertain due to its complex nature, but has been studied by existing techniques. It is undisputed that asphaltene is composed mainly of polyaromatic carbon, i.e. polycondensed aromatic benzene units with oxygen, nitrogen, and sulfur, combined with minor amounts of a series of heavy metals, particularly vanadium and nickel which occur in porphyrin structures. Asphaltenes are today widely recognized as soluble, chemically altered fragments of kerogen which migrated out of the source rock during oil catagenesis. Asphaltenes are dispersed in reservoir petroleum fluid as nanoaggregates. Heavy oils and tar sands contain much higher proportions of asphaltenes than do medium-API oils or light oils. Condensates are virtually devoid of asphaltenes.
Computer-based modeling and simulation techniques have been developed for estimating the properties and/or behavior of petroleum fluid in a reservoir of interest. Typically, such techniques employ an equation of state (EOS) model that represents the phase behavior of the petroleum fluid in the reservoir. Once the EOS model is defined, it can be used to compute a wide array of properties of the petroleum fluid of the reservoir, such as: gas-oil ratio (GOR) or condensate-gas ratio (CGR), density of each phase, volumetric factors and compressibility, heat capacity and saturation pressure (bubble or dew point). Thus, the EOS model can be solved to obtain saturation pressure at a given temperature. Moreover, GOR, CGR, phase densities, and volumetric factors are byproducts of the EOS model. Transport properties, such as heat capacity or viscosity, can be derived from properties obtained from the EOS model, such as fluid composition. Furthermore, the EOS model can be extended with other reservoir evaluation techniques for compositional simulation of flow and production behavior of the petroleum fluid of the reservoir, as is well know in the art. For example, compositional simulations can be helpful in studying (1) depletion of a volatile oil or gas condensate reservoir where phase compositions and properties vary significantly with pressure below bubble or dew point pressures, (2) injection of non-equilibrium gas (dry or enriched) into a black oil reservoir to mobilize oil by vaporization into a more mobile gas phase or by condensation through an outright (single-contact) or dynamic (multiple-contact) miscibility, and (3) injection of CO2 into an oil reservoir to mobilize oil by miscible displacement and by oil viscosity reduction and oil swelling.
In the past few decades, fluid homogeneity in a hydrocarbon reservoir has been assumed. However, there is now a growing awareness that fluids are often heterogeneous or compartmentalized in the reservoir. A compartmentalized reservoir consists of two or more compartments that may be in hydraulic communication. Two types of reservoir compartmentalization have been identified, namely vertical and lateral compartmentalization. Vertical compartmentalization usually occurs as a result of faulting or stratigraphic changes in the reservoir, while lateral compartmentalization results from horizontal barriers. Gravity, chemical forces, molecular and thermal diffusion, natural convection, biodegradation, adsorption, and external fluxes can also lead to non-equilibrium hydrocarbon distribution in a reservoir.
Reservoir compartmentalization, as well as non-equilibrium hydrocarbon distribution, can significantly hinder production and can make the difference between an economically-viable field and an economically-nonviable field. Techniques to aid an operator to accurately describe reservoir compartments and their distribution, as well as non-equilibrium hydrocarbon distribution, can increase understanding of such reservoirs and ultimately raise production.
Although the importance of reservoir compartmentalization, as well as non-equilibrium hydrocarbon distribution, on production has been recognized, conventional pressure-depth plots and pressure gradient analysis are still performed with traditional straight-line regression schemes. This process may, however, be misleading as fluid compositional changes and compartmentalization give distortions in the pressure gradients, which result in erroneous interpretations of fluid contacts or pressure seals.
Downhole fluid analysis (DFA) measurements provide a useful tool to determine the compositional gradients at downhole conditions in real time. An example of a well logging tool suitable for capturing fluid samples for compositional data analysis is the Modular Dynamic Formation Tester (MDT) available from Schlumberger Technology Corporation of Sugar Land. Tex., USA. The MDT tool provides a controlled channel of hydraulic communication between the reservoir fluid and the wellbore and allows withdrawal of small amounts of formation fluid through a probe that contacts the reservoir rock (formation). Such downhole fluid sampling is advantageous because the sampling is more accurate downhole. More specifically, in the event that the sampling pressure is above the saturation pressure, the fluid will be in a single phase, ensuring that the original composition is being analyzed. For pressures below the saturation pressure, a measurement of the properties of the liquid phase in the oil zone and the associated gas above it will yield a more accurate sampling than a sample recombined at the surface. Indeed, it may be difficult to retain the sample in the state in which it existed downhole when it is retrieved to surface. Historically, fluid samples collected by well logging tools were brought to the surface for analysis in the laboratory. However, recent developments in the MDT tool have made possible the direct measurement of fluid properties downhole during the pump-out or sampling sequence, which, is referred to herein as “downhole fluid analysis.” Details of the MDT tool and its capabilities for downhole fluid analysis may be obtained with reference to commonly owned U.S. Pat. Nos. 3,859,851; 4,994,671; 5,167,149; 5,201,220; 5,266,800; 5,331,156; and 7,081,615, all of which are incorporated herein by reference.
Downhole fluid analysis is advantageous because information is provided in real time, in contrast to a laboratory analysis that may take several days, or surface wellsite analysis that may result in undesirable phase transitions as well as the loss of key constituents. However, the compositional and property gradients (e.g., the compositions of CO2, C1, C2, C3-C5, and C6+, and GOR) measured by DFA tools may not provide information that can be used to accurately detect compartmentalization and/or non-equilibrium hydrocarbon distribution in the reservoir of interest.